Why we made this change

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We’re all constantly sharing billions of pieces of data about our shopping habits, where we like to eat, and places we visit often, as well as the messages, pictures, and video we post on social media. Companies want to use this data to provide us better and new services—and of course, sell us more stuff.

Creating the computer systems and software needed to sift through billions of pieces of data is among today’s biggest challenges—and opportunities—for the high-technology industry.

From a company’s point of view, the most critical aspect of this process is time to insight—that is, how long it takes to obtain actionable insights from the data they’ve captured and analyzed. For example, imagine that you’re on a flight that’s running late. During the delay, the flight attendant offers you a complimentary drink that just happens to be your favorite cocktail. That kind of service requires real-time analysis of data to quickly obtain insights about your preferences and habits.

Creating the computer systems and software needed to sift through all that data and provide faster time to insight is among today’s biggest challenges—and opportunities—for the high-technology industry. Corporate customers in this space are turning to tech companies for help in building bigger computer systems and sophisticated software to enable fast, effective big-data analytics.

Today, big-data computer systems and software are increasingly being built on an innovative, collaborative open-source foundation. In fact, 170 technology companies, many of which compete with each other, have formed a consortium to provide some of the technologies needed to fuel big-data analytics. The new organization, the OpenPOWER Foundation, allows these companies to collaborate in an open ecosystem.

As one example: Several OpenPOWER members, including IBM, NVIDIA, Mellanox, and Xilinx, recently joined forces to release the IBM Power Systems LC line of servers. These powerful new servers, built around open innovation, provide technologies that accelerate data analytics using hardware accelerators such as graphics processing units (GPUs) and field programmable gate arrays (FPGAs).

Allegiant Travel is an example of a company that’s already using such technology effectively. The leisure-travel company, which was already using Power Systems technology with the POWER8 chip, paired that capability with Red Hat Enterprise Linux and OpenPOWER expertise.

The result: Allegiant Travel better understands the meaning in the consumer data that it’s gathering and how to use that information quickly and effectively. Bryan O’Neil, Allegiant Travel’s director of data architecture, is an advocate of building such cognitive systems not just for immediate gain, but for long-term improvement: “I like to think in longer, broader terms, as opposed to what the problem of the day is,” he says.

Meanwhile, we can all expect to see other businesses, such as hotels, restaurants, and retailers (online and off), continue analyzing our habits—and improving and customizing their services as a result. And the next time my flight gets delayed, I’ll look forward to that complimentary cocktail.

Sumit Gupta is Vice President, High-Performance Computing and OpenPOWER, at IBM. Previously, he was General Manager for GPU-Accelerated Data Center Computing at NVIDIA, Product Marketing Manager for Tensilica, and Entrepreneur-in Residence for Tallwood Venture Capital, among other positions.

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Sumit Gupta is Vice President, High-Performance Computing and OpenPOWER, at IBM. Previously, he was General Manager for GPU-Accelerated Data Center Computing at NVIDIA, Product Marketing Manager for Tensilica, and Entrepreneur-in Residence for… More Tallwood Venture Capital, among other positions.

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